Prompt Library Hardening with Claude Code: MCP Tool Boundary
A production playbook for prompt library hardening in cross-industry operations using Claude Code: mcp tool boundary, run-scoped inputs, logs, typed results, and artifacts.
Audience: AI platform teams maintaining reusable prompts
The problem
AI platform teams maintaining reusable prompts need prompt library hardening to run repeatedly against prompt folders, examples, red-team cases, and tool rules. In cross-industry operations, the pain is not one good answer; it is repeatability, auditability, exception handling, and evidence that survives handoff.
Implementation path
Expose only the MCP tools needed for prompt library hardening, validate tool arguments, keep credentials in the owning service, and log each call outside the sandbox.
Tradeoffs and failure modes
Narrow tool boundaries reduce agent flexibility, but make the integration reviewable and supportable. For prompt library hardening, the practical test is whether a second run can be debugged, retried, and consumed by a product without reading the raw agent transcript.
Tool policy
tool: prompt-library-hardening_lookup
agent: Claude Code
input_scope: /skill/.argo/inputs
credential_owner: broker
log_arguments: true
network_policy: allowlisted
Run this on Argo